Background

Objective

The objective of this analysis is to estimate DALYs lost in New York City due to the following major categories of conditions (with about 100 conditions in total within these categories):

  • Major depression
  • Alcohol use
  • Marijuana use
  • Heroin use
  • Cocaine use
  • Stimulant use
  • Sedative use
  • Tranquilizer use

Definition of Key Terms

DALY

Disability-adjusted life years. The DALY is a year of life lived in perfect health and consists of two elements: YLLs and YLDs. The DALY is a measure of overall disease burden, expressed as the number of years lost due to ill-health, disability or early death. It was developed in the 1990s as a way of comparing the overall health and life expectancy of different countries.

\[ DALY = YLL + YLD \]

YLL

Years of life lost. Years of life lost is an estimate of the average years a person would have lived if he or she had not died prematurely.

\[ YLL = (Number\ of\ deaths) * (Standard\ life\ expectancy\ at\ age\ of\ death\ in\ years) \]

YLD

Years of life lost due to disability. This is the morbidity component of the DALY score. To estimate YLD for a particular cause in a particular time period, the number of incident cases in that period is multiplied by the average duration of the disease and a weight factor that reflects the severity of the disease on a scale from 0 (perfect health) to 1 (dead). The basic formula for YLD is the following:

\[ YLD = (number\ of\ incident\ cases) * (disability\ weight) * (average\ duration\ of\ disease) \]

Methods

Data Sources

  • 2013 NYCHANES - prevalence estimates
  • 2002-2008 NSDUH - drug use prevalence estimates
  • 2013 NYC Vital Statistics - mortality estimates
  • 2010 Global Burden of Disease Study - national YLD/YLL rates
  • 2013 NYC American Community Survey - population estimates

The challenge with using NYCHANES and NSDUH data to estimate the prevalence of a condition is that the n may be too small. To increase their utility of these surveys, we will aggregate age groups into the following strata: childhood (0-14), late adolescence/early adulthood (15-24), adulthood (25-64), and later life (65+).

DALY Estimation

YLLs

To estimate compute NYC YLLs, we will use NYC mortality counts stratified by age, sex, and race. In concodrance with the literature on DALY estimation, life expectancy estimates based on the life expectancy in Japan (82.5 years for women and 80.0 years for men) were used for the calculation of YLL. In order to remain consistent with the methodology of the 2010 Global Burden Disease Study, no age weighting or discounting was applied.

YLDs

To compute NYC YLDs, we will use the two approaches described below:

2005 NYC DOHMH / Michaud (2006)

In order to compare the magnitude of the DALY scores to the 2005 NYC DOHMH study, we will replicate the previous study’s methodology, which was based on Michaud CM, et al. The burden of disease and injury in the United States 1996. Population Health Metrics 2006,4:11.

“For NYC YLD, U.S. Census Bureau population estimates for New York City in 2005 by sex were used to calculate years lived with disability (YLD) by applying national YLD rates and ratios from the Michaud et al. study. If the national YLL:YLD ratio was less than 10, then the NYC YLD was equal to the national YLD:YLL ratio multiplied by NYC YLL. If the national YLD:YLL ratio was greater than or equal to 10 (producing unreliable City estimates), then NYC YLD was equal to the national YLD rate multiplied by the NYC population.”

Implementing the Michaud approach will thus require the following data elements:

  • NYC Population by age, sex
  • National YLD rates by age, sex
  • NYC YLLs by age, sex

In order to remain consistent with the demographic weighting approach used by NYC DOHMH for the 2013 NYCHANES data, NYC population estimates were obtained from the 2013 American Community Survey, which is available on the NYC Department of City Planning website. Since the data from the Michaud study are from 1996 and patterns of disease and disability have changed, we will update the approach using national YLD/YLL rates from the 2010 Global Burden of Disease Study.

Prevalence-based YLDs

Years lived with a disability (YLD) due to each disease can be calculated on the basis of either the incidence or the prevalence of the disease. The initial GBD studies estimated YLD on the basis of the incidence of each disease. Thus, in the 1990 study for example, the YLD estimates measured the future loss of health resulting from disease episodes that began in 1990. One advantage of this approach is that it is consistent with that used for mortality: YLL measure the future loss of life resulting from deaths in a particular year.

The 2010 GBD study adopted the alternative approach and calculated YLD based on the prevalence of the impairments resulting from each disease in the year for which the estimates are made. This approach has the advantage that it assigns YLD to the ages at which they are lived, rather than to the age at which the disease episode that produced them began.

Because prevalence is approximately incidence x duration, prevalence YLD for a condition (across all ages) is approximately the same as the no frills incidence YLD. As such, we can estimate YLDs using the following formula:

\[ YLD = (number\ of\ prevalent\ cases) * (disability\ weight) \]

We can estimate the number of prevalent cases for each condition using survey data from 2013 NYCHANES. Annual prevalence for drug use can be estimated using data from 2002-2008 NSDUH. Disability weights can be extracted from the 2010 Global Burden of Disease study.However, we should note that the prevalence YLD for a condition may be quite different in magnitude to the incidence-based YLD, depending on how age weighting and discounting are applied. As such, comparisons to previous NYC DALY studies should be done with caution.

Further information about estimating DALYs can be found from the Global Burden of Disease concept paper (WHO, 2006).

Disease Rankings

Since our goal is to communicate the burden of diseases in New York City, we will rank each condition in decreasing order of the DALY score. We will also test the stability of the rankings by comparing the results generated from the Michaud approach and the prevalence-based YLDs approach. Moreover, since the 2010 GBD study also provides 95% confidence intervals around point estimates for disability weights and national YLD/YLL rates, further stability checks can be conducted by reporting DALY estimations with their respective upper and lower bounds.

However, we should note that since the DALY estimations are not inclusive of all disease conditions, we will not be able to report our findings as the “top X conditions contributing to DALYs.” Instead, we can only report mental health DALYs in reference to other highly prevalent chronic diseases.

Estimation of Substance Use Dependence

Prevalence estimates of substance use cannot be directly substituted for prevalence of drug dependence or abuse disorders. We make the following assumptions about the average proportion of dependence among users (National Addiction Centre, 2003):

  • Alcohol - 15.4%
  • Cocaine - 16.7%
  • Heroin - 23.1%
  • Cannabis - 9.1%

Estimation of Major Depressive Disorder Using PHQ-9

Prevalence estimates for 2-week depression was obtained for 2013 NYCHANES. While 2-week depression prevalence would lead to underestimation of 1-year depression, the use of PHQ-9 scores can also overestimate both MDD and any depressive disorder due to its low positive predictive value (~55%) for PHQ-9 scores below 10, the cutoff between mild and moderate depression (Kroenke, 2002). To adjust for this in the prevalence-based YLD approach, we did not consider PHQ-9 scores below 10 and assumed - from expert opinion - that only half of those with PHQ-9 scores above 10 were actually diagnosed with MDD.

Sensitivity Analysis

In order to validate the Michaud approach, we will use 2005 NYC mortality estimates from the previous DOHMH to test the stability of our DALY rankings. However, since age-weighting is no longer used by the 2010 GBD due to ethical concerns, we suspect the magnitude of 2013 NYC DALYs to be slightly higher than that of the 2005 NYC DALYs.

DALY Estimation

Michaud YLD Approach

This section contains an implementation of the Michaud approach described in the above methods section. We first create a search index containing all the disease conditions of interest.

This search index is then fed through the calculateDALY workhorse function to estimate DALYs for each disease condition. The result is a data.frame object containing the following columns: cause_name, sex, yll, yld, yld_upper, yld_lower, daly, daly_upper, daly_lower.

Prevalence-Based YLD Approach

Similar to the section, we implement the prevalence-based YLD approach here using the same search index.

Results

Michaud YLD Approach

Raw results for this approach can be found under the results directory under the filename nyc_daly_michaud.csv. The file can be opened in Excel and manipulated with a pivot table for aggregation and stratification purposes.

2013 NYC DALY Estimates, Total

cause_name yll yld yld_upper yld_lower daly daly_upper daly_lower
Ischemic heart disease 122326 11569 16786 7589 133895 139112 129915
Major depressive disorder 0 83953 121100 55076 83953 121100 55076
Other musculoskeletal disorders 2837 74190 89035 58823 77027 91872 61660
Anxiety disorders 0 52051 75105 34951 52051 75105 34951
Chronic obstructive pulmonary disease 13123 21960 34847 12251 35083 47970 25374
Diabetes mellitus 17984 15001 21700 9912 32985 39684 27896
Lung cancer 29658 449 791 211 30107 30449 29869
Hypertensive heart disease 27201 891 1549 429 28092 28749 27630
Osteoarthritis 129 26968 41201 16316 27097 41330 16445
Ischemic stroke 15957 10924 13521 8485 26881 29478 24443
Asthma 2863 23162 37090 12510 26025 39953 15373
High blood pressure 0 23051 31082 15615 23051 31082 15615
Alzheimer’s disease and other dementias 13613 9286 12343 6555 22899 25956 20168
Lower respiratory infections 20554 1095 1661 671 21649 22215 21225
Alcohol use disorders 4673 14942 22992 9083 19615 27665 13757
Opioid use disorders 10654 7272 10935 4299 17925 21588 14953
Bipolar affective disorder 0 16820 25727 10012 16820 25727 10012
Breast cancer 13773 2548 3856 1647 16321 17629 15420
HIV/AIDS 13117 2764 4487 1422 15881 17604 14539
Colon and rectum cancers 14377 985 1645 567 15362 16022 14944
Cannabis use disorders 0 14303 21780 8642 14303 21780 8642
Cocaine use disorders 6738 7054 13145 3321 13792 19883 10059
Poisonings 12390 69 182 10 12459 12573 12400
Homicide 10945 NA NA NA 10945 NA NA
Other drug use disorders 5373 5245 8900 2829 10619 14273 8202
Congenital anomalies 5752 1049 1648 631 6801 7400 6383
Motor vehicle accidents 5318 1224 1846 783 6542 7163 6100
Amphetamine use disorders 0 2773 4845 1347 2773 4845 1347

  • Ischemic heart disease is the leading cause of disease in 2013, but has a wide range of uncertainty
  • Disaggregated drug use disorders ranked relatively low, particuarly for non-alcohol-related substances
  • Major depressive disorder just missed the top 10 cutoff

2013 NYC DALY Estimates, Male

cause_name sex yll yld yld_upper yld_lower daly daly_upper daly_lower
Ischemic heart disease Male 59171 4986 7246 3254 64158 66417 62425
Major depressive disorder Male 0 29122 42380 19172 29122 42380 19172
Other musculoskeletal disorders Male 971 22446 28679 15890 23417 29650 16861
Anxiety disorders Male 0 16888 24380 11291 16888 24380 11291
Chronic obstructive pulmonary disease Male 5818 10412 16696 5717 16229 22514 11535
Diabetes mellitus Male 8870 6836 10019 4468 15706 18889 13338
Lung cancer Male 15346 215 367 110 15560 15713 15456
Alcohol use disorders Male 3694 11614 17842 7105 15308 21536 10799
Hypertensive heart disease Male 13357 310 555 145 13668 13912 13503
Opioid use disorders Male 7701 5136 7623 3096 12837 15324 10797
Asthma Male 1464 10463 16739 5641 11927 18203 7105
Ischemic stroke Male 6876 4987 6197 3854 11863 13073 10730
High blood pressure Male 0 10872 14946 7183 10872 14946 7183
HIV/AIDS Male 8508 1906 3004 1036 10413 11512 9543
Lower respiratory infections Male 9756 463 710 279 10219 10466 10035
Cocaine use disorders Male 4910 4824 8895 2304 9734 13805 7214
Osteoarthritis Male 62 9384 14597 5661 9445 14658 5722
Homicide Male 9185 NA NA NA 9185 NA NA
Poisonings Male 8881 53 134 9 8934 9015 8890
Colon and rectum cancers Male 7021 432 712 250 7452 7733 7271
Bipolar affective disorder Male 0 7449 11473 4414 7449 11473 4414
Other drug use disorders Male 3874 3519 5948 1914 7393 9823 5789
Alzheimer’s disease and other dementias Male 3823 2529 3391 1788 6352 7215 5612
Motor vehicle accidents Male 3805 830 1252 533 4634 5057 4338
Cannabis use disorders Male 0 4486 6858 2705 4486 6858 2705
Cannabis use disorders Male 0 4486 6858 2705 4486 6858 2705
Congenital anomalies Male 3042 537 834 325 3579 3877 3367
Amphetamine use disorders Male 0 1711 2950 839 1711 2950 839

  • Alcohol use disorders rises to the #4 slot
  • Homicide and accidental deaths such as poisonings and motor vehicle accidents rise in rankings

2013 NYC DALY Estimates, Female

cause_name sex yll yld yld_upper yld_lower daly daly_upper daly_lower
Ischemic heart disease Female 63155 6582 9540 4335 69737 72695 67490
Major depressive disorder Female 0 54832 78719 35904 54832 78719 35904
Other musculoskeletal disorders Female 1866 51743 60357 42933 53609 62223 44799
Anxiety disorders Female 0 35163 50725 23660 35163 50725 23660
Chronic obstructive pulmonary disease Female 7306 11548 18151 6534 18854 25457 13840
Osteoarthritis Female 67 17585 26605 10655 17652 26672 10722
Diabetes mellitus Female 9114 8165 11681 5444 17279 20795 14558
Alzheimer’s disease and other dementias Female 9790 6757 8951 4767 16547 18741 14557
Breast cancer Female 13773 2548 3856 1647 16321 17629 15420
Ischemic stroke Female 9081 5937 7324 4632 15018 16405 13713
Lung cancer Female 14313 234 424 100 14547 14737 14413
Hypertensive heart disease Female 13843 581 994 284 14424 14837 14127
Asthma Female 1399 12699 20350 6869 14099 21750 8268
High blood pressure Female 0 12180 16136 8433 12180 16136 8433
Lower respiratory infections Female 10798 632 951 391 11430 11748 11189
Bipolar affective disorder Female 0 9371 14254 5598 9371 14254 5598
Colon and rectum cancers Female 7356 554 933 317 7910 8289 7673
HIV/AIDS Female 4609 859 1483 386 5468 6092 4995
Opioid use disorders Female 2953 2135 3311 1203 5088 6264 4156
Alcohol use disorders Female 980 3327 5149 1978 4307 6129 2958
Cocaine use disorders Female 1828 2230 4250 1017 4058 6078 2845
Poisonings Female 3509 16 48 1 3525 3557 3510
Other drug use disorders Female 1499 1726 2951 915 3225 4450 2413
Congenital anomalies Female 2710 513 814 305 3222 3524 3015
Cannabis use disorders Female 0 2665 4032 1616 2665 4032 1616
Cannabis use disorders Female 0 2665 4032 1616 2665 4032 1616
Motor vehicle accidents Female 1513 394 594 249 1907 2107 1762
Homicide Female 1760 NA NA NA 1760 NA NA
Amphetamine use disorders Female 0 1062 1895 508 1062 1895 508

  • Breast cancer makes the top 3
  • Alzheimer's disease and other dementias ranks very high
  • Drug-related disorders get pushed to the bottom

Prevalence-Based YLD Approach

Raw results for this approach can be found under the results directory under the filename nyc_daly_prevalence.csv. The file can be opened in Excel and manipulated with a pivot table for aggregation and stratification purposes.

2013 NYC DALY Estimates, Total

cause_name yll yld yld_upper yld_lower daly daly_upper daly_lower
Ischemic heart disease 122326 30186 34498 24197 152512 156824 146523
Alcohol use disorders 4673 136164 188737 92528 140837 193410 97202
Major depressive disorder NA 125830 168883 86154 125830 168883 86154
Other arthritis NA 88591 123561 59838 88591 123561 59838
Chronic obstructive pulmonary disease 13123 64253 90690 43170 77376 103813 56293
Osteoarthritis 129 57587 80319 38896 57716 80447 39025
Breast cancer 13873 24769 34626 16765 38642 48499 30638
Lung cancer 29664 4937 6902 3342 34602 36567 33006
Anxiety NA 30752 49203 17426 30752 49203 17426
Cocaine use disorders 6738 22333 32846 13958 29071 39584 20696
Opioid use disorders 10654 18069 22636 12939 28723 33290 23593
Diabetes mellitus 17984 10119 12143 8095 28104 30127 26080
Cannabis use disorders NA 24991 34562 16939 24991 34562 16939
Asthma 2863 20058 33430 11143 22922 36294 14007
Colon and rectum cancers 14383 4471 6251 3027 18854 20634 17409
Ischemic stroke 15957 1820 3207 953 17777 19164 16911
Amphetamine use disorders NA 4025 5986 2451 4025 5986 2451
Stimulant use disorders NA 2549 3790 1552 2549 3790 1552
High blood pressure NA 0 0 0 0 0 0
Sedative use NA 0 0 0 0 0 0
Sedative use disorders NA 0 0 0 0 0 0
Tranquilizer use disorders NA 0 0 0 0 0 0
  • Major depressive disorder ranks number one, beating out the number two slot by almost twice the number of DALYs However, DALY estimates appear to be unstable, taking a wide range of possible values.
  • Not enough information to calculate DALY estimates for sedative use, stimulant use, tranquilizer use.

2013 NYC DALY Estimates, Male

cause_name sex yll yld yld_upper yld_lower daly daly_upper daly_lower
Alcohol use disorders Male 3694 72958 101127 49577 76651 104820 53271
Ischemic heart disease Male 59171 13079 14947 10484 72250 74119 69655
Major depressive disorder Male NA 40352 54452 27533 40352 54452 27533
Chronic obstructive pulmonary disease Male 5818 32495 45865 21833 38313 51683 27650
Other arthritis Male NA 31037 43288 20963 31037 43288 20963
Osteoarthritis Male 62 18723 26114 12647 18785 26176 12708
Opioid use disorders Male 7701 9980 12502 7146 17681 20203 14847
Cocaine use disorders Male 4910 12568 18484 7855 17478 23394 12765
Lung cancer Male 15351 1926 2692 1304 17277 18044 16655
Diabetes mellitus Male 8870 4770 5724 3816 13640 14594 12686
Anxiety Male NA 11399 18238 6459 11399 18238 6459
Colon and rectum cancers Male 7021 1835 2565 1242 8856 9586 8263
Asthma Male 1464 7269 12115 4038 8733 13579 5502
Cannabis use disorders Male NA 8054 11138 5459 8054 11138 5459
Cannabis use disorders Male NA 8054 11138 5459 8054 11138 5459
Ischemic stroke Male 6876 608 1071 318 7484 7947 7195
Amphetamine use disorders Male NA 2514 3740 1531 2514 3740 1531
Stimulant use disorders Male NA 1610 2394 980 1610 2394 980
Breast cancer Male 100 0 0 0 100 100 100
High blood pressure Male NA 0 0 0 0 0 0
Sedative use disorders Male NA 0 0 0 0 0 0
Tranquilizer use disorders Male NA 0 0 0 0 0 0

  • Alcohol use disorders rises in proportion to major depressive disorder

2013 NYC DALY Estimates, Female

cause_name sex yll yld yld_upper yld_lower daly daly_upper daly_lower
Major depressive disorder Female NA 85478 114432 58621 85478 114432 58621
Ischemic heart disease Female 63155 17107 19551 13713 80262 82705 76867
Alcohol use disorders Female 980 63206 87610 42951 64186 88590 43931
Other arthritis Female NA 57555 80274 38875 57555 80274 38875
Chronic obstructive pulmonary disease Female 7306 31758 44824 21337 39063 52130 28643
Osteoarthritis Female 67 38863 54204 26250 38931 54271 26317
Breast cancer Female 13773 24769 34626 16765 38542 48399 30539
Anxiety Female NA 19353 30965 10967 19353 30965 10967
Lung cancer Female 14313 3011 4210 2038 17324 18523 16351
Diabetes mellitus Female 9114 5349 6419 4279 14464 15533 13394
Asthma Female 1399 12789 21315 7105 14189 22715 8505
Cocaine use disorders Female 1828 9765 14361 6103 11593 16189 7931
Opioid use disorders Female 2953 8090 10134 5793 11042 13087 8745
Ischemic stroke Female 9081 1212 2136 635 10294 11217 9716
Colon and rectum cancers Female 7362 2636 3685 1784 9998 11047 9146
Cannabis use disorders Female NA 4442 6142 3010 4442 6142 3010
Cannabis use disorders Female NA 4442 6142 3010 4442 6142 3010
Amphetamine use disorders Female NA 1510 2246 920 1510 2246 920
Stimulant use disorders Female NA 939 1396 572 939 1396 572
High blood pressure Female NA 0 0 0 0 0 0
Sedative use Female NA 0 0 0 0 0 0
Sedative use disorders Female NA 0 0 0 0 0 0
Tranquilizer use disorders Female NA 0 0 0 0 0 0

Michaud YLDs vs. Prevalence-Based YLDs: Side-by-Side Comparison

Total

Male

Female

Disease Conditions with Small Sample Sizes

##                    cause_name                      sequlae    sex    age
## 25              Breast cancer                Breast cancer   Male 20-39 
## 26              Breast cancer                Breast cancer   Male 40-59 
## 27              Breast cancer                Breast cancer   Male   60+ 
## 28              Breast cancer                Breast cancer Female 20-39 
## 36      Cocaine use disorders                  Cocaine use Female   60+ 
## 37   Colon and rectum cancers     Colon and rectum cancers   Male 20-39 
## 38   Colon and rectum cancers     Colon and rectum cancers   Male 40-59 
## 39   Colon and rectum cancers     Colon and rectum cancers   Male   60+ 
## 40   Colon and rectum cancers     Colon and rectum cancers Female 20-39 
## 41   Colon and rectum cancers     Colon and rectum cancers Female 40-59 
## 42   Colon and rectum cancers     Colon and rectum cancers Female   60+ 
## 55       Opioid use disorders                   Heroin use   Male 20-39 
## 56       Opioid use disorders                   Heroin use   Male 40-59 
## 57       Opioid use disorders                   Heroin use   Male   60+ 
## 58       Opioid use disorders                   Heroin use Female 20-39 
## 59       Opioid use disorders                   Heroin use Female 40-59 
## 60       Opioid use disorders                   Heroin use Female   60+ 
## 67     Ischemic heart disease       Ischemic heart disease   Male 20-39 
## 70     Ischemic heart disease       Ischemic heart disease Female 20-39 
## 73                Lung cancer                         Lung   Male 20-39 
## 74                Lung cancer                         Lung   Male 40-59 
## 75                Lung cancer                         Lung   Male   60+ 
## 76                Lung cancer                         Lung Female 20-39 
## 77                Lung cancer                         Lung Female 40-59 
## 78                Lung cancer                         Lung Female   60+ 
## 87  Amphetamine use disorders          Methamphetamine use   Male 20-39 
## 88  Amphetamine use disorders          Methamphetamine use   Male 40-59 
## 89  Amphetamine use disorders          Methamphetamine use   Male   60+ 
## 90  Amphetamine use disorders          Methamphetamine use Female 20-39 
## 91  Amphetamine use disorders          Methamphetamine use Female 40-59 
## 92  Amphetamine use disorders          Methamphetamine use Female   60+ 
## 101 Major depressive disorder          moderate depression   Male   60+ 
## 105 Major depressive disorder moderately severe depression   Male 20-39 
## 106 Major depressive disorder moderately severe depression   Male 40-59 
## 107 Major depressive disorder moderately severe depression   Male   60+ 
## 111           Other arthritis              Other arthritis   Male 20-39 
## 125 Major depressive disorder            severe depression   Male 20-39 
## 126 Major depressive disorder            severe depression   Male 40-59 
## 127 Major depressive disorder            severe depression   Male   60+ 
## 128 Major depressive disorder            severe depression Female 20-39 
## 130 Major depressive disorder            severe depression Female   60+ 
## 139           Ischemic stroke              Ischemic stroke   Male 20-39 
## 140           Ischemic stroke              Ischemic stroke   Male 40-59 
## 141           Ischemic stroke              Ischemic stroke   Male   60+ 
## 142           Ischemic stroke              Ischemic stroke Female 20-39

Sensitivity Analysis

2005 NYC DALY Estimates, Total

cause_name yll yld yld_upper yld_lower daly daly_upper daly_lower
Ischemic heart disease 142893 13658 19810 8966 156550 162703 151859
Major depressive disorder 0 83953 121100 55076 83953 121100 55076
Other musculoskeletal disorders 2885 74223 89073 58852 77108 91957 61737
Anxiety disorders 0 52051 75105 34951 52051 75105 34951
HIV/AIDS 29554 6239 10198 3244 35793 39752 32798
Chronic obstructive pulmonary disease 12759 21453 34059 11961 34212 46818 24720
Lung cancer 32684 485 883 225 33169 33567 32909
Diabetes mellitus 17422 15059 21862 9929 32481 39284 27351
Asthma 3187 24307 38885 13140 27494 42073 16327
Osteoarthritis 149 26968 41201 16316 27117 41350 16465
Hypertensive heart disease 25274 835 1519 384 26108 26792 25658
Lower respiratory infections 24303 1312 1981 809 25615 26284 25112
High blood pressure 0 23051 31082 15615 23051 31082 15615
Alcohol use disorders 4921 15510 23839 9449 20431 28761 14370
Breast cancer 17147 3054 4732 1956 20201 21880 19103
Bipolar affective disorder 0 16820 25727 10012 16820 25727 10012
Colon and rectum cancers 14606 1055 1774 618 15661 16380 15224
Poisonings 15023 88 230 13 15111 15253 15036
Homicide 14663 NA NA NA 14663 NA NA
Cannabis use disorders 0 14303 21780 8642 14303 21780 8642
Ischemic stroke 0 12250 14808 9752 12250 14808 9752
Opioid use disorders 0 11530 17272 6864 11530 17272 6864
Cerebrovascular disease 8046 2585 3094 2076 10630 11139 10122
Drug use disorders 2326 6231 8780 4202 8557 11106 6528
Alzheimer’s disease and other dementias 4452 3053 4060 2154 7505 8512 6606
Congenital anomalies 5859 1111 1741 672 6971 7600 6531
Cocaine use disorders 0 6792 12484 3277 6792 12484 3277
Motor vehicle accidents 3135 512 775 325 3647 3910 3460
Amphetamine use disorders 0 2773 4845 1347 2773 4845 1347

2005 NYC DALY Estimates, Male

cause_name sex yll yld yld_upper yld_lower daly daly_upper daly_lower
Ischemic heart disease Male 62241 5253 7628 3433 67494 69869 65674
Major depressive disorder Male 0 29122 42380 19172 29122 42380 19172
Other musculoskeletal disorders Male 604 22433 28657 15884 23036 29261 16487
HIV/AIDS Male 17948 4244 6583 2371 22192 24532 20319
Alcohol use disorders Male 4438 13308 20434 8139 17747 24873 12577
Lung cancer Male 17348 238 411 121 17586 17759 17469
Anxiety disorders Male 0 16888 24380 11291 16888 24380 11291
Chronic obstructive pulmonary disease Male 5605 10302 16528 5655 15907 22133 11260
Diabetes mellitus Male 8440 6526 9561 4265 14967 18002 12705
Hypertensive heart disease Male 11866 268 491 120 12134 12357 11986
Homicide Male 11903 NA NA NA 11903 NA NA
Asthma Male 1409 10463 16739 5641 11871 18148 7050
Lower respiratory infections Male 10657 513 786 311 11170 11443 10968
Poisonings Male 11035 70 176 12 11105 11210 11047
High blood pressure Male 0 10872 14946 7183 10872 14946 7183
Osteoarthritis Male 59 9384 14597 5661 9443 14656 5720
Opioid use disorders Male 0 8139 12049 4928 8139 12049 4928
Bipolar affective disorder Male 0 7449 11473 4414 7449 11473 4414
Colon and rectum cancers Male 6478 421 680 250 6899 7158 6728
Ischemic stroke Male 0 5693 6885 4521 5693 6885 4521
Cocaine use disorders Male 0 4601 8347 2259 4601 8347 2259
Cannabis use disorders Male 0 4486 6858 2705 4486 6858 2705
Cannabis use disorders Male 0 4486 6858 2705 4486 6858 2705
Cerebrovascular disease Male 3085 1042 1250 834 4126 4334 3918
Congenital anomalies Male 3108 550 855 333 3658 3963 3441
Drug use disorders Male 1620 1512 2134 1006 3132 3755 2626
Motor vehicle accidents Male 2060 323 489 206 2383 2549 2267
Alzheimer’s disease and other dementias Male 1280 832 1114 589 2112 2395 1869
Amphetamine use disorders Male 0 1711 2950 839 1711 2950 839

2005 NYC DALY Estimates, Female

cause_name sex yll yld yld_upper yld_lower daly daly_upper daly_lower
Ischemic heart disease Female 80652 8404 12182 5533 89056 92834 86184
Major depressive disorder Female 0 54832 78719 35904 54832 78719 35904
Other musculoskeletal disorders Female 2281 51790 60415 42969 54071 62696 45250
Anxiety disorders Female 0 35163 50725 23660 35163 50725 23660
Breast cancer Female 17147 3054 4732 1956 20201 21880 19103
Chronic obstructive pulmonary disease Female 7154 11151 17530 6307 18305 24685 13461
Osteoarthritis Female 90 17585 26605 10655 17674 26694 10745
Diabetes mellitus Female 8982 8533 12301 5665 17514 21282 14646
Asthma Female 1779 13844 22146 7499 15623 23925 9277
Lung cancer Female 15336 247 472 104 15583 15808 15440
Lower respiratory infections Female 13646 799 1196 498 14445 14841 14144
Hypertensive heart disease Female 13407 567 1028 264 13974 14436 13671
HIV/AIDS Female 11606 1995 3615 873 13601 15221 12479
High blood pressure Female 0 12180 16136 8433 12180 16136 8433
Bipolar affective disorder Female 0 9371 14254 5598 9371 14254 5598
Colon and rectum cancers Female 8128 634 1095 368 8762 9223 8496
Ischemic stroke Female 0 6556 7923 5231 6556 7923 5231
Cerebrovascular disease Female 4961 1543 1844 1242 6504 6805 6203
Drug use disorders Female 706 4719 6645 3197 5424 7351 3902
Alzheimer’s disease and other dementias Female 3172 2221 2946 1565 5393 6118 4737
Poisonings Female 3988 18 54 1 4006 4042 3989
Opioid use disorders Female 0 3390 5223 1936 3390 5223 1936
Congenital anomalies Female 2751 562 886 339 3313 3637 3090
Homicide Female 2760 NA NA NA 2760 NA NA
Alcohol use disorders Female 483 2202 3405 1310 2685 3888 1793
Cannabis use disorders Female 0 2665 4032 1616 2665 4032 1616
Cannabis use disorders Female 0 2665 4032 1616 2665 4032 1616
Cocaine use disorders Female 0 2191 4138 1017 2191 4138 1017
Motor vehicle accidents Female 1074 189 287 119 1264 1361 1193
Amphetamine use disorders Female 0 1062 1895 508 1062 1895 508

Discussion

Limitations

There are key limitations to this analysis. First and foremost, the magnitude of the DALY scores should be interpreted and reported with caution. Due to the small sample size of NYC prevalence estimates and the uncertainty around disability weights and national YLL/YLD rates for some conditions, DALY estimates can assume a wide range of values, changing how one condition ranks against the others (for example, alcohol use disorders and diabetes mellitus). For this reason, DALY magnitudes obtained via Michaud approach and the Prevalence-based YLDs cannot be directly compared.

Moreover, the accuracy of DALY estimations suffers from potential biases introduced in the data collection and computation processes. For example, comorbidities with respect to chronic diseases means that DALY estimates based on Vital Statistics mortality counts are overestimating the contribution of YLLs. Summation of prevalence YLDs across all causes can result in overestimation of the total average severity-weighted health state prevalence because of comorbidity between conditions (Mathers, 2006). Over-reporting of some conditions due to misclassification (e.g. where symptoms such as joint pain are labeled as osteoarthritis or occasional wheezing as asthma), under-reporting of undiagnosed conditions (e.g. most mental health problems), and lack of information on condition severity (resulting in high prevalences due to inclusion of very minor conditions or minor symptoms) may also contribute to biased DALY estimates.

In order to convey the uncertainty around our estimates, we visualize the range of values that NYC DALY estimates can take for each condition.

Sensitivity Analysis

NYC DALY rankings and magnitudes using the Michaud approach are fairly consistent using both 2005 and 2013 NYC mortality counts. Moreover, the Michaud approach implemented in this analysis replicated the 2005 NYC DALY estimates from the previous NYC DOHMH study, producing comparable rankings. However, since age-weighting is no longer used due to ethical concerns, the 2013 NYC DALYs are slightly larger in magnitude. Recommendations for future work include running simulations to test the stability of DALY rankings for an even wider range of assumptions.

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